# Liver fibrosis cell-based assay platform: integrating patient-derived fibrotic liver ECM with primary stellate cells, Kupffer cells, and hepatocytes to accelerate anti-fibrotic drug development > **NIH NIH R44** · XYLYX BIO, INC. · 2024 · $370,020 ## Abstract PROJECT ABSTRACT Xylyx is developing engineered human liver fibrotic lesions as a predictive cell-based assay platform to address the lack of in-vitro drug testing assay products containing human fibrotic liver ECM in the market. Liver fibrosis is a progressive disease process underlying multiple chronic liver diseases (NAFLD, NASH, ASH, hepatitis C) and leads to cirrhosis, which causes over 1 million deaths/year worldwide. NASH alone affects 4% of the global population, and 30 million people in USA, where annual mortality exceeds 48,000. No drug is approved to treat liver fibrosis, underscoring the inadequacy of current liver fibrosis models and the necessity of better drug testing assays. The extracellular matrix (ECM) is known to play critical roles in liver fibrogenesis and fibro-proliferation. Animal models are poor predictors of liver fibrosis in humans, and predictive in-vitro models of liver fibrosis are not commercially available, leaving a significant unmet need and market gap/opportunity for a physiologically-relevant in-vitro platform that enables high-fidelity cell-based phenotypic assays in engineered human liver fibrotic lesions. This SBIR Fast Track will support development and validation studies for commercialization of a liver fibrosis cell-based assay platform containing engineered human liver fibrotic lesions shown to be consistent with patient data. The technological innovation is the product’s engineered human liver fibrotic lesions stemming from proprietary methods for isolating and integrating acellular human fibrotic liver ECM that has the pathological properties of human diseased liver tissue. Our approach integrates NASH patient-derived stellate cells, Kupffer cells, and hepatocytes in standardized human primary fibrotic liver ECM, enabling predictive in-vitro assays on engineered human fibrotic liver lesions – a unique product and major competitive advantage over all existing assays, which lack human liver fibrotic ECM and histopathology. Our goal is to validate and commercialize a standard liver fibrosis cell-based assay platform for predictive in-vitro modeling of human liver fibrosis to reduce dependence on animal models and de-risk preclinical decision-making. Specific aims: (1) Perform multi-omics and histomorphologic profiling of engineered human fibrotic liver lesions; (2) Determine histologic, molecular, phenotypic effects of Kupffer cells and hepatocytes on engineered human liver fibrotic lesions; (3) Evaluate quality and consistency of engineered human liver fibrotic lesions assay platform; (4) Test anti-fibrotic drug candidates using engineered human liver fibrotic lesions assay platform. After successful completion of the Fast Track project, Xylyx will commercialize the liver fibrosis assay platform for scientists in pharma companies in need of predictive fibrotic disease models for drug screening, thus reducing the massive costs associated with late-stage attrition due to poor efficacy, and facilitating de... ## Key facts - **NIH application ID:** 11008126 - **Project number:** 1R44DK139877-01A1 - **Recipient organization:** XYLYX BIO, INC. - **Principal Investigator:** John David O'Neill - **Activity code:** R44 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2024 - **Award amount:** $370,020 - **Award type:** 1 - **Project period:** 2024-09-01 → 2025-08-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/11008126 ## Citation > US National Institutes of Health, RePORTER application 11008126, Liver fibrosis cell-based assay platform: integrating patient-derived fibrotic liver ECM with primary stellate cells, Kupffer cells, and hepatocytes to accelerate anti-fibrotic drug development (1R44DK139877-01A1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/11008126. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*